Nickel-based super alloy grinding optimisation using a hybrid multi attribute decision making method based on entropy, AHP and TOPSIS

Abstract

ABSTRACT Nickel-based superalloy grinding, as well as selecting the appropriate operational parameters, is one of the major challenges in machining engineering. The conducted research consists of two sections. The first section presents a systematic experimentation, which has been carried out to qualitatively and quantitatively investigate nickel-based superalloy grinding. Vitrified CBN grinding wheels, along with a rotary diamond cup dresser, were utilised to conduct the experiments with the workpiece of Inconel 738. Specific grinding energy, G-ratio and surface roughness were indicated as three major machining outputs, while the inputs were the dressing conditioning and grinding parameters. In the following, the effects of different operational parameters were relatively ranked according to their weighted impact on the grinding performance using hybrid multi-attribute decision-making (MADM) methods. For this purpose, a combination of three techniques: Analytic Hierarchy Process (AHP), Entropy and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was utilised to select the most appropriate grinding conditions, while considering the conflicting effect of the different dressing and grinding parameters. The results indicate that specific energy can be an important criterion for evaluating the process efficiency. The changes in G-ratio and surface roughness have the same trends, as opposed to specific grinding energy mutation. The grinding parameters are summarised in equivalent chip thickness. Our findings show that dresser cross feed rate, along with equivalent chip thickness, has the greatest impact on the grinding process efficiency.